code: def get_word_list_token(
      text: str, word_lists: Tuple[List[str], List[str]]
  ) -> str:
      """
      Return a control token corresponding to gender within text.
  
      :param text:
          text to consider for control token
      :param word_lists:
          tuple of lists for male-specific and female-specific words
  
      :return token:
          return control token corresponding to input text.
      """
      m_list, f_list = word_lists
      text = format_text(text)
      m_cnt = 0
      f_cnt = 0
      for word in text.split(" "):
          if word in m_list:
              m_cnt += 1
          if word in f_list:
              f_cnt += 1
  
      if f_cnt == 0 and m_cnt == 0:
          return "f0m0"
      elif f_cnt == 0 and m_cnt > 0:
          return "f0m1"
      elif f_cnt > 0 and m_cnt == 0:
          return "f1m0"
      else:
          return "f1m1"
  
file_path: ParlAI/parlai/tasks/genderation_bias/utils.py
imports: from collections import deque
  import random
  from parlai.core.loader import load_teacher_module
  from parlai.core.message import Message
  from parlai.core.opt import Opt
  from typing import List, Tuple
label_desc: Use image node_id 2 for calling a global function with example usage: get_word_list_token(text, word_lists) and returns: str, str, str, str